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Record W2016612282 · doi:10.1115/ht2008-56458

Validation of Dynamic Models for an Air-Cooled CPU Chip Cooling Device

2008· article· en· W2016612282 on OpenAlexaff
R. Zhang, C. Zhang, Jin Jiang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsComputational fluid dynamicsChipTemperature controlWater coolingThermalComputer scienceMechanical engineeringSimulationEngineeringAerospace engineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

In this paper, the proposed novel technique using computational fluid dynamics (CFD) approach to design control systems is validated experimentally for a chip cooling device. Both experimental approach and CFD simulations are employed to extract the dynamic characteristics from the non-linear chip cooling system around a specific operating point, which are then used to construct the linear dynamic model for the chip cooling system. The linear dynamic model has two inputs, the heat load generated by the chip and the cooling fan voltage. The output is the temperature of the case housing the chip. The results from the linear dynamic model obtained by the CFD approach are compared with those obtained experimentally under the same dynamic conditions to validate the feasibility of using the CFD approach to design a control system for a thermal-fluid system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.601
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.244
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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